Difference between revisions of "Help:Glossary"
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=== People Tracking and Counting === | === People Tracking and Counting === | ||
=== Person detection=== | === Person detection=== | ||
− | * | + | * Person detection denotes the ability of a [[Help:Glossary#Software|software]] application to estimate (as in, provide a statistical probability) whether an object in the camera image is a person. Generally, it is able to indicate the position of the person in the image. Person detection systems can be used in basic analytics scenarios, where for example the presence of people is counted. Moreover, object detection algorithms can be used to track individuals between video frames, although they generally have a hard time tracking occlusions (people walking in front of others, hiding them from the camera) and specific people across multiple camera viewpoints. Person detection does not obtain any information about individuals faces. |
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=== Products === | === Products === | ||
=== Public Spaces === | === Public Spaces === |
Revision as of 15:52, 25 May 2022
This page will give a short overview over the most important terms used in the Wiki.
A[ ]
Audio Recognition[ ]
- The ability of a software to identify/understand certain sounds. From a technological perspective, software processes audio relatively similarly to how video is processed: rather than feeding an image, a spectrogram is used as input for the software.
B[ ]
Behavioural Data[ ]
- Behavioural data is the data collected related to the way in which individuals uniquely behave (facial expressions, body movements, voice, etc.).
Biometric Data[ ]
- Biometric data is all data related to the body, which can be used to identify or monitor individuals or groups of individuals and is impossible or very difficult to alter (face, fingerprints, iris, etc.).
Biometric Identification[ ]
- The use of biometrical or behavioural data to identify a person.
Biometric Mass Surveillance[ ]
- Biometric Mass Surveillance is a form of monitoring, tracking, or processing of personal (biometric and behavioural) data of individuals indiscriminately and in a generalised manner without a prior criminal suspicion (FRA, 2019).
- Additionally, this surveillance occurs at a distance, in a public space and in a continuous or ongoing manner by checking them against data stored in a database.
C[ ]
Controlled Images[ ]
- Controlled images are images that are captured for the purpose of processing, aimed at optimal positions and lighting conditions. They are for example taken at a police station, or at a photographer’s studio with strict requirements, and are either contained in databases that precede the introduction of a facial recognition system (e.g., driver’s license databases) or are specifically designed to match high criteria of biometric systems (i.e., photographs for biometric passports).
Cooperative Searches[ ]
- Cooperative searches involves voluntary consent to a search. This is contrary to non-cooperative searches.
D[ ]
Datasets[ ]
- A dataset is a structured collection and storage of data. For the Wiki, it often involves the structured collection and storage of biometric data, such as fingerprints, facial images etc.
Deployments[ ]
- For the Wiki, deployments are all instances in which biometric data is being collected in public spaces.
E[ ]
Emotion recognition[ ]
F[ ]
Facial Recognition (Identification)[ ]
Facial Recognition (Verification/Authentication)[ ]
Forensic Facial Recognition[ ]
G[ ]
Gait Recognition[ ]
H[ ]
I[ ]
Identification[ ]
Institutions[ ]
J[ ]
K[ ]
L[ ]
Live Facial Recognition[ ]
M[ ]
Machine Learning[ ]
N[ ]
Neural Networks[ ]
Non-Cooperative Searches[ ]
O[ ]
P[ ]
People Tracking and Counting[ ]
Person detection[ ]
- Person detection denotes the ability of a software application to estimate (as in, provide a statistical probability) whether an object in the camera image is a person. Generally, it is able to indicate the position of the person in the image. Person detection systems can be used in basic analytics scenarios, where for example the presence of people is counted. Moreover, object detection algorithms can be used to track individuals between video frames, although they generally have a hard time tracking occlusions (people walking in front of others, hiding them from the camera) and specific people across multiple camera viewpoints. Person detection does not obtain any information about individuals faces.